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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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latency constraints. - Federated and distributed learning for RAN hardware infrastructure management. o Knowledge of autonomous AI systems based on agents. Indicative skills/experience: - Multi-Agent
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custom assistant creation and autonomous agents. Expected Skills/Proficiency Level Agile Methodology - Developing Code Review - Developing Debugging - Developing JIRA - Developing Microservices
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
in artificial intelligence (AI) for settings involving multiple interacting decision-makers---whether autonomous AI agents, humans, or a combination of both. Applications include mixed-autonomy
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, artificial intelligence and autonomous vehicles, advanced vehicle efficiency and sustainability, smart manufacturing, and human–machine interaction. The successful candidate will demonstrate a strong
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and interpret diagnostic tests, and diagnose/manage chronic as well as acute patient problems. Facilitate and deliver care to a specific subset of patients collaboratively and autonomously. Obtain and
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techniques, dockerization mechanisms, and scripting. Experience with ROS, Python, C++, Docker and YAML scripts is necessary. The candidate will also conduct research in the broad area of autonomous multi-agent
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Description We welcome applications from researchers working across a wide range of AI domains – including Symbolic, Generative, Agentic, and Physical AI – as well as frontier research areas such as causality
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facilitate active scientific exchange and foster a good atmosphere, and therefore play a big role in our team. Learn more about us here: https://swa.cs.univie.ac.at/ Your future tasks: You actively participate
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highly desirable) AI/ML for predictive modeling and inverse design of nanomaterials Autonomous laboratories for materials synthesis and characterization Generative models, reinforcement learning, and agent